Abstract
Glioblastoma exhibits different characteristics and outcomes across different age groups, making age-specific analysis crucial for personalized treatment strategies. Traditional approaches often treat glioblastoma as a homogeneous disease, failing to capture the age-related variations in tumor biology and patient outcomes. In this work, we present a comprehensive radiomics-based study investigating age-related differences in glioblastoma characteristics.
Our approach leverages quantitative imaging features to characterize glioblastoma across different age groups, from young adults to elderly patients. The study analyzes multiple radiomics features including texture, shape, and intensity-based descriptors extracted from brain MRI scans. We investigate how these features vary across age groups and their correlation with clinical outcomes.
We evaluate our approach on a large cohort of glioblastoma patients stratified by age groups. Results demonstrate significant differences in radiomics features across age groups, with distinct patterns emerging for young, middle-aged, and elderly patients. These differences correlate with variations in survival outcomes and treatment responses.
The findings from this study provide valuable insights into age-related glioblastoma characteristics and could inform the development of age-specific treatment strategies and prognostic models.
BibTeX
@article{li2017age,
title={Age groups related glioblastoma study based on radiomics approach},
author={Li, Zeju and Wang, Yuanyuan and Yu, Jinhua and Guo, Yi and Zhang, Qi},
journal={Computer Assisted Surgery},
year={2017},
publisher={Taylor \& Francis},
doi={10.1080/24699322.2017.1378722}
}